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Land Use Policy 26 (2009) 535–544

Contents lists available at ScienceDirect

Land Use Policy

journa l homepage: www.e lsev ier .com/ locate / landusepol

lobalization and population drivers of rural-urban land-use change inhihuahua, Mexico

ate Currit a,∗, William E. Easterlingb

Department of Geography, Texas State University-San Marcos, 601 University Drive, San Marcos, TX 78666-4616, USADepartment of Geography, The Pennsylvania State University, 116 Deike Building, University Park, PA 16802, USA

r t i c l e i n f o

rticle history:eceived 21 June 2006eceived in revised form 31 July 2008ccepted 4 August 2008

eywords:

a b s t r a c t

A thorough examination of the causes of land-use change is necessary to effectively deal with the mag-nitude of changes across the globe. Chihuahua, Mexico is experiencing rapid land-use changes due toprocesses of globalization. The emergence of Mexico’s maquiladora program is an indicator of economicglobalization that has had far-reaching social and environmental consequences. This article examinespopulation and income patterns from 1970 to 2000 as part of a hierarchical system and tests whether

ierarchical systemsopulation and income concentrationhihuahuaexico

or not processes of globalization can be detected in the patterns. Findings indicate that population andincome concentrate primarily in Juarez, while simultaneously deconcentrating in most other municipiosof the State. Moreover, these patterns correlate with patterns of maquiladora concentration. Additionalfindings identify proximity to the US and established urban centers as drivers of population concentration.These findings support the notion that patterns and processes of globalization are important drivers ofpopulation and income concentration at the local level in Chihuahua, Mexico. Finally, the findings supportthe conceptualization of population land-use and income concentration as part of a hierarchical system.

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The magnitude and intensity of important land-use changescross the globe requires a thorough examination of their causes.ecause of the broad impact of land-use changes, an understand-

ng of their causes has the potential for enhancing human qualityf life, improving management of environmental degradation andood production, and increasing global security. Often, multipleauses interact in a complex system to produce unexpected land-se changes. In order to foresee and effectively manage unexpected

and-use changes, care must be taken to identify all the interact-ng drivers of change. Lambin et al. (2001) discuss the challengef properly identifying land-use drivers by noting several mythsf land-use changes and then outlining their actual drivers. Notinghat identification of the actual drivers is not a simple linear process,hey identify globalization as a contemporary driver cross-cutting

any significant land-use changes.Patterns and processes of globalization influence contemporary

and-use trends. Globalization is the set of processes by whichlaces across the globe are joined into social, economic, and envi-

∗ Corresponding author. Tel.: +1 512 245 3198; fax: +1 512 245 8353.E-mail addresses: currit@txstate.edu (N. Currit), billeasterling@psu.edu

W.E. Easterling).

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264-8377/$ – see front matter © 2008 Elsevier Ltd. All rights reserved.oi:10.1016/j.landusepol.2008.08.001

© 2008 Elsevier Ltd. All rights reserved.

onmental networks of interaction (Held et al., 1999). Globalizationrocesses evolve as more places become more interconnected, asarriers to interconnectedness are removed, or as flows of infor-ation increase between places (World Bank, 2005). Some notable

and-use outcomes of globalization processes include (1) interna-ional environmental agreements to regulate shared water or airesources; (2) imposed structural adjustments that lead to changesn the intensity of agricultural production; (3) increased trans-ortation and financial accessibility to remote places of the globe;nd (4) the relocation of large human populations and the accel-rated growth of cities, leading to spatial changes in resourcese.

Demographic factors are notable drivers of land-use change thatay derive of globalization processes. The IPAT formula is a long-

tanding theory of population–environment interaction (DeHartnd Soule, 2000; Dietz and Rosa, 1994; Ehrlich and Holdren, 1971).PAT generally examines endogenous total population increases oropulation density as causes of environmental impacts. Recentesearch focuses on rural household demographics, like house-old size, fertility, on-farm population density, age and mortality.

he goal of these studies is to improve our understanding ofopulation–environment relationships while avoiding simplisticodels of human–environment interaction. de Sherbinin et al.

2008) provide an excellent review and synthesis of scholarlypproaches to rural household demographics.

5 nd Use Policy 26 (2009) 535–544

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Fig. 1. The number and distribution of maquiladora establishments in Mexico in2000. The point symbols are located at municipio centroids where maquiladoraestablishments were reported at the municipio level. Municipios with less than2mtt

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schy of interacting processes. Aguilar and Ward (2003) traceMexico’s patterns of population distribution to economic strate-gies implemented during different periods beginning in the1940s.

36 N. Currit, W.E. Easterling / La

The US-Mexico border is one region where significant demo-raphic changes are occurring. The present pattern of populationhange along the US-Mexico border is that of an increasingly con-entrated urban population on the Mexico-side of the border, withidespread spillover into the United States (Esparza et al., 2001).

he current and future trajectory of population change along theorder depends largely on socio-economic trends that began nearlyour decades ago and that are arguably linked to patterns of increas-ng global interconnectedness. Understanding these populationand-use patterns is essential to effective land management at allevels along the US-Mexico border.

We argue that an analysis of changing population and incomeoncentrations in the border State of Chihuahua will offer insightsor effective management of contemporary, rural-urban land-usehange in a globally interconnected system. This research will bearticularly useful for determining how changing demographicsay influence resource demands in a globally connected rural-

rban system. Therefore, the purpose of this article is to examineopulation and income patterns at regional and local levels in thetate of Chihuahua and test whether or not forces of globalizationan be detected in the patterns.

lobalization and Mexican population trends

We consider industrial land-use the dominant driver behindopulation and income concentration in Mexico. The largest con-entration of industrial land-use is found in Mexico City. Themplementation of the maquiladora program was one of the firstteps towards industrialization along the US-Mexico border. Popu-ations were relatively small along the US-Mexico border during theormative years of the maquiladora program. Over time, however,nd in conjunction with changes in industrial activity nationally,he degree of population concentration in Mexico City slowed andities along the US-Mexico border became population destinations.his section explores these national and border trends in order torovide a context for the analysis of population and income con-entration in Chihuahua.

he Maquiladora Program

In 1943 the US enacted US Public Law 45 (1943), a guestorker program commonly called the “Bracero program” that

egally allowed Mexican citizens to enter the US and work in agri-ulture. The purpose of this law was to sustain US crop productionuring wartime while many US males were overseas and unavail-ble for agricultural labor. Four and one half million individualontracts were filed for temporary employment in the US duringhe program’s tenure, but the program drew much larger num-ers of Mexicans from the interior of the country than could beupported (Andreas, 1994). In 1964, the US terminated the Bracerorogram sending all Mexican guests back to Mexico. The result waslarge unemployed Mexican population on the Mexico-side of theS-Mexico border.

Mexico announced the Border Industrialization Program (BIP),ommonly called the maquiladora program, in 1965. A maquiladoras a corporation located in Mexico that is permitted by the Mex-can government to temporarily import, tariff free, all goodsecessary for the transformation, manufacture, or repair of prod-cts destined for export (INEGI, 2001). Maquiladoras are oftenoreign-owned, but with Mexican management. In developing the

aquiladora program, Mexico sought to employ the large unem-loyed population along its northern border, and to take advantagef multi-national corporations seeking relatively low wage laborersn proximity to the large US consumer market. Maquiladoras con-entrated in individual cities along the border with little expansion

bamn

maquiladora establishments are not recorded as having any maquiladoras. Allaquiladora establishments not reported at the municipio level are reported as addi-

ional maquiladoras at the state level. Municipios with maquiladoras are labeled forhe State of Chihuahua.

o nearby regions or the interior of Mexico1 (Fig. 1). In this article,e treat maquiladoras as indicators of Mexico’s globalization along

he US-Mexico border because they trade their products on interna-ional markets and often derive non-labor production factors fromutside of Mexico.

From 1974 to 1980, national growth in three maquiladora indica-ors of global interconnectedness was minimal. The average annualrowth rates were 6% for the number of maquiladora establish-ents, 9% for the number of maquiladora employees, and 7% for

he value added to maquiladora products (Fig. 2). In 1982, the yearf the great peso devaluation, all national maquiladora variablesad negative growth. Signs of growth were apparent in 1983 and by984 significant growth occurred in all three maquiladora variables.igh annual growth rates continued for most of the next 6 years,eaking in 1987 (establishments: 25% and employees: 22%) or 1988value added: 36%). Growth rates then decreased until the mid-990s, even becoming negative for the number of establishmentsn 1994 (−1%) and value added in 1995 (−17%). The implementa-ion of NAFTA in 1994 bolstered the maquiladora industry so that by996 high positive growth rates returned and continued until 2000.

Maquiladora trends in Chihuahua mimic those at the nationalevel (Fig. 2). Juarez was the only municipio with maquiladorasn the State of Chihuahua until 1980, when maquiladoras werestablished in the municipio of Chihuahua. In 1999, small numbersf maquiladoras opened in three other municipios. Maquiladoras,owever, continue to be most concentrated in Juarez (Fig. 1).

ndustrialization nationally

Population trends across Mexico over the past several decadesuggest the influence of a global–national–regional hierar-

1 Originally maquiladoras were required to locate within 20 km of the US-Mexicoorder (South, 1990). Regulations were later relaxed and maquiladoras could locatenywhere within Mexico except Mexico City and Guadalajara. During the last decadeaquiladoras expanded into smaller cities in border states and into larger cities in

on-border states.

N. Currit, W.E. Easterling / Land Us

Fig. 2. Indicators of growth in the maquiladora industry in Mexico: (A) number ofmaquiladora establishments; (B) number of maquiladora employees; and (C) valueadded to maquiladora products (US dollars adjusted to the year 2000). The solidbsm

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stdRlwthose at the national level, but with different, local outcomes. In

lack lines and right-side y-axis represent Mexican national trends. The colors repre-ent, from darkest to lightest, the municipios of Juarez, Chihuahua and the remainingunicipios of the State of Chihuahua.

Between 1940 and 1970, Mexico implemented economic poli-ies that created industries to produce goods as import-substitutes.he focus on import substitution industrialization (ISI) was driveny internal incentives and increased demand for Mexican goods asresult of import shortages during World War II. ISI strategies dur-

ng this period led to an average annual growth rate of 7.8% in theanufacturing sector. At the same time, agricultural production

ropped from 23% of GDP to 11% of GDP. These industrializationrocesses led to the concentration of capital intensive industries

n Mexico City and little industrial presence in other parts of theountry. Demographically, industrial concentration led to acceler-ted population growth in Mexico City and precluded significantopulation growth in other parts of Mexico. Aguilar and Rodriguez1994/1995) note that in 1970 only one medium-sized Mexican city

xisted.

Mexico experienced periodic financial crises in the 1970s. Mex-co became a net oil importer for the first time in 1971, even thoughhe production of crude oil was increasing modestly, and remained

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e Policy 26 (2009) 535–544 537

net importer until 1975. Poor fiscal policy during this period ledo trade deficits, market uncertainty, capital flight, and balance ofayments difficulties, culminating in the devaluation of the peso by8% in 1976. Total oil exports had an average annual growth rate of4.6% for the period 1977–1980. Mexico’s oil-export economy wasragile, however, because it was not accompanied by sound fiscalolicy.

The end of Mexico’s ISI came in 1982 and signaled a change inopulation patterns across the country. Mexico plunged into eco-omic crisis because of a drop in global oil prices and the absence oflarge agricultural sector, which led to sharp trade deficits. The pesoas devalued, inflation was 100% per annum, and external debt wasS$ 85 billion (Aguilar, 1997). In response, Mexico implemented

tructural changes supporting export-oriented industrialization.mphasis was placed on the private sector and the export of non-il goods, even though Mexico experienced a brief oil boom in theate 1980s. In 1986, Mexico lowered inflation rates, reduced publicpending and lowered its financial deficit. Foreign direct invest-ent (FDI) increased in regions outside Mexico City and industries

hat had concentrated in Mexico City were faced with increasedompetition from these outside regions.

Demographic outcomes of industrial deconcentration includedreater employment and income inequality within Mexico City,ncreased employment opportunities outside Mexico City andecreased migration to Mexico City (Aguilar, 1999; Jones, 2001;raizbord et al., 2003). Although Mexico City remains the largestity in Mexico, numerous “medium-sized” cities experiencedarge annual growth rates during this period, some as large as4% (Aguilar and Rodriguez, 1994/1995). Aguilar and Rodriguez1994/1995) quantify “a deconcentration process towards the leastrbanized areas in each region [of Mexico],” including northernexico. Esparza et al. (2001) note that “Mexico’s northern border

ities have undergone enormous population growth, mainly due tonternal migration” (pg. 20) driven by growth in the maquiladorandustry. The North American Free Trade Agreement (NAFTA)urther intensified this trend of deconcentration by increasing pop-lation concentration in Mexican border states (Peach and Molina,002). By implication, growth of Chihuahua’s population is part ofexico’s deconcentration trend.In spite of observed urban deconcentration at the national

evel, concentration in Chihuahua is not likely uniform across thetate—it appears to be concentrated in Ciudad Juarez. Esparza etl. (2004) describe “unprecedented population growth” (pg. 124)n Juarez since the maquiladora program began. They also notehat a large proportion of the population works in maquiladorandustries. In fact, according to the 2000 census, Ciudad Juarezecame part of what Aguilar and Rodriguez (1994/1995) classify ashe “big metropolitan population” category. Esparza et al. (2004)nd Fuentes and Cervera (2006) additionally attribute changes inrban form, including polycentric development and the presencef peripheral squatter settlements, to industrialization processesinked to the maquiladora industry. Bae (2003) notices similarrends for the Tijuana-San Diego metropolitan complex.

Even though Ciudad Juarez’s growth is likely indicative of ahift from metropolitan growth to non-metropolitan growth athe national level, it may also be indicative of rural populationeconcentration at the state level. This suggests that Aguilar andodriguez’s findings of deconcentration are scale dependent and

eaves open the possibility that population and income patternsithin Chihuahua derive from globalization patterns similar to

act, Anderson and Gerber (2008) describe three potential driversf population concentration along the border: (1) manufacturingctivity, (2) a significant urban core, and (3) a border crossing. Wexpect to find a rural-urban dynamic of population and income

5 nd Us

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sfoeuwere first collected in 1974, almost a decade after the begin-ning of the Maquiladora program, by the Mexican Instituto deEstadistica, Geografia e Informatica (INEGI) and are publishedinfrequently in book form (INEGI, 2000a,b, 1997, 1994, 1990b,1983).

Table 1Municipio-level variables used in the analysis of population and income concentra-tion in Chihuahua, Mexico

Code Variable Description

Ma Maquiladora establishments Number of individual maquiladorasE Maquiladora employees Total employees of maquiladorasV Value added to maquiladora

productsAdjusted to year 2000 US dollars

P Total population Includes all population sub-categoriesM Migrant population Population born in entity

38 N. Currit, W.E. Easterling / La

oncentration that is unique to Chihuahua because of its interactionith national and global patterns and processes of globalization.

The trends of enormous population growth in Mexico’s north-rn border cities attributed to growth in the maquiladora industryrive our efforts to use maquiladoras as indicators of globaliza-ion that may influence local patterns of population and incomeoncentration in Chihuahua. We expect concentration to be mostronounced where maquiladoras are located. We expect deconcen-ration to occur in the remainder of the municipios of the State. Wergue that this (de)concentration pattern emerges due to Ciudaduarez’s ties to the global economy. Such an emergent pattern mayonstrain possibilities for rural livelihoods and promote significantand-use changes.

ierarchical systems, systemic change and resilience

While an approach based on a nested hierarchy may suggesthe use of long-standing central place theory (CPT), we considerts assumptions untenable in this case. For example, CPT assumes

normative landscape that does not exist in Chihuahua. CPTocuses on production markets and their service areas. Such a focuss insufficient in a highly dynamic human–environment systemike Chihuahua (Manson and O’Sullivan, 2006). Lastly, CPT treatsll markets as part of a regional system and ignores the influ-nce of global cities, like Ciudad Juarez (Esparza and Krmenec,996).

In this article, we conceptualize Chihuahua’s population andncome trends as part of a coupled human–environment system,f which land-use systems are a component (Bicik et al., 2001).he basic premises of a hierarchical systems approach are that (1)nteracting sub-systems function as a single, nested system, (2)ertain sub-systems dominate at specific geographic and tempo-al scales, (3) new patterns and processes emerge at intermediateeographic scales, and (4) these systems are highly dynamic—theyre not rigid structures (Manson and O’Sullivan, 2006; Peterson,000; Levin, 1998). These premises have important implicationsor systemic resilience to external perturbations (Vogel et al.,007).

We choose to use a hierarchical systems approach for thisnalysis for three reasons. First, we seek a theoretical frameworkhat gives equal footing to human and environmental compo-ents of a coupled system because we expect this analysis toontribute to broader investigations of the complex relationshipsetween globalization, demographics and environmental change inhihuahua.

Second, recent research identifies systems composed of hier-rchically organized patterns and processes that operate acrosseographic and temporal scales (Allen and Holling, 2002; Peterson,002). In these systems, patterns develop and are maintainedhrough the interaction of processes in a nested hierarchyEasterling and Kok, 2002). We believe that the application of theseoncepts to population and income concentration in Chihuahuaill elucidate hierarchical processes of global–national–local inter-

ction that would not otherwise be apparent.The patterns and processes at any level in a hierarchy are the

roducts of dynamic patterns and processes at adjacent scalesO’Neil, 1988). Large-scale systems are often conceptualized asonstraints on smaller scale systems, while small-scale systemsrovide the mechanism of change in larger scale systems. More

mportant than hierarchical structure, however, is the flow of

nergy and information between adjacent levels in a nested hier-rchy. Patterns and processes emerge at intermediate scales thatan be measured, modeled and predicted based on this cross-scalexchange (Muller, 1996; Costanza and Patten, 1995). Emergent pat-erns self-organize from interactions among, or flows between,

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e Policy 26 (2009) 535–544

atterns and processes at adjacent scales and are dependent onontinual flows of energy and information.

Third, globalization is creating previously unknown challengesor sustaining land-use systems. Change is ubiquitous in a systemhere patterns and processes interact across scales in non-

inear fashion. Concepts of vulnerability and resilience are gainingalience within the hierarchical systems approach because theyave important implications for dealing with globalization pro-esses. A vulnerable system is one that is susceptible to change fromiscrete external perturbations. A resilient system absorbs externalerturbations and persists unchanged. Recently, a call was made tossess the resiliency of hierarchical systems dominated by global-zation processes: “we need to learn more about how the impactsf globalization cascade up and down scales affecting adaptabil-ty, resilience, and vulnerability from the local to the global level”Young et al., 2006). To enhance resilience requires knowledge ofhe interactions between hierarchical scales, and the developmentf a diversity of interconnections between scales (Walker et al.,002). To gain such knowledge, one must ask: What sub-systemsre missing? Which are poorly understood? What systemic changesight result if an existing pattern or process is altered? In social

ystems, institutions must develop the ability to balance the needsf system components and to be flexible in problem solving (Cashnd Moser, 2000).

We contend that conceptualizing rural-urban populationynamics within a globalized setting as a hierarchical system willeveal causal relationships that suggest management practices fornhancing resilience to unexpected change in the land-use system.mplementing practices based on these relationships may enhancehe resilience of rural livelihoods in Chihuahua and avoid unde-irable land-use change in rural and urban settings. The abstractrinciples of hierarchical organization and process discussed abovere rarely persuasively demonstrated in empirical land-use stud-es. Here we empirically analyze local and regional population andncome concentration in Chihuahua as outcomes of patterns androcesses of globalization.

ata and methods

Three maquiladora variables are collected from hardcopy cen-uses and entered electronically into a database system forurther analysis (Table 1). These variables are (1) the numberf maquiladora establishments, (2) the number of maquiladoramployees, and (3) the value added to maquiladora prod-cts. Aggregated yearly data on the maquiladora industry

Urban population Population centers greater than or equalto 2500

Employed population Total employed populationIncome Total income (adjusted to year 2000 US

dollars)

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mdAtributions, including Nuevo Casas Grandes and Cuauhtémoc, bothof which contain medium-sized cities. Most remaining municip-ios experienced consistent deconcentration. This pattern led to awidening concentration gap between Juarez and almost every othermunicipio.

Table 2Decadal Hoover indices for all maquiladora, population, and income categories

1970 1980 1990 2000

Ma (A) – 94.30 94.30 89.14E (A) – 94.30 94.30 92.13V (A) – – – 92.74P (A) 53.97 57.77 62.83 67.82

N. Currit, W.E. Easterling / La

The analysis of population and income census data spanshe period 1970–2000, covering the period during which the

aquiladora program began and expanded. Decadal general pop-lation censuses for Mexico are collected by INEGI. As with theaquiladora data, the general population censuses are not com-

letely available in electronic format prior to the 2000 censusINEGI, 2000c, 1990a, 1980, 1970). Therefore, we extract all gen-ral population data from microfilm and manually enter them inton electronic database. These variables include total population,igrant population, urban population, employed population, and

otal income (Table 1).2

Parametric statistical techniques are of limited use in thisase because the population and income data exhibit a highegree of multi-collinearity, and maquiladora data are highlykewed. As a consequence, regressing population or income onaquiladora establishments violates key assumptions and would

roduce biased results (Gould, 1970). Therefore, we use non-arametric techniques to determine the degree of concentrationf population, income and maquiladora variables and their inter-elationships. We also select a method to assess possible factorsnderlying the population and income patterns.

Specifically, we use the Hoover index to determine the extent ofopulation, income, and maquiladora concentration in ChihuahuaShumway and Otterstrom, 2001; Rogers and Raymer, 1998; Longnd Nucci, 1997; Hoover, 1941). It measures the degree to whichpopulation varies from a perfectly uniform distribution. It has a

ower limit of 0 and approaches 100 as the total population con-entrates in a single geographic place within a region. This valueepresents the exact percentage of the population that would haveo be redistributed to other places within the region in order toreate a uniform distribution. The Hoover index is calculated as:

=∑

|Ai − Pi|2

(1)

here Ai is the areal proportion of the ith place in the region, andi is the population proportion of the ith place in the region.

The Hoover index is not a spatial measure of concentration—iteasures the total degree of concentration only. One alternatives

or calculating a spatially explicit Hoover index is to retain the dif-erence between areal and population proportions for each placesee Eq. (1)) as additional data in the database. The differences the contribution of a place within the region to the overalloover index value. Negative (positive) values indicate concentra-

ion (deconcentration)—places where the population would have toecrease (increase) to achieve uniformity. Mapping the contribu-ion of each place to the overall concentration using this alternativerovides the disaggregated, spatial view of concentration needed inur study. Any population variable can be used in the aggregate andpatially explicit Hoover index calculations, including populationub-categories.

We use the Spearman Rank correlation coefficient to determinehe extent to which patterns of population and income concentra-ion spatially covary with patterns of maquiladora concentration.he Spearman Rank correlation coefficient is a non-parametric

easure of association suitable for data that do not exhibit a nor-al distribution, like population concentration data, but that can be

anked. Positive correlation coefficients, indicating that high (low)anks in one variable correspond to high (low) ranks in the other

2 Twelve variable combinations of population and income concentration areerived from these variables. An example of the notation used to identify a variableombination is “P (A).” This notation should be read as “total population concen-rated within the area.” Another example is “M (P).” This notation should be read asmigrant population concentrated within the total population.”

MMUUUWWWIII

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e Policy 26 (2009) 535–544 539

ariable, are expected between patterns of maquiladora, popula-ion and income concentrations.

Lastly, principal components analysis is performed on the pop-lation and income data only to reduce the data dimensionalityo a set of interpretable underlying factors. These factors may beartly responsible for Chihuahua’s population land-use and incomeatterns. Principal components are inferred from the correlationatrix of population and income variables, where each component

s a linear combination of the five census variables (total, migrant,rban and employed populations, and income). A varimax rotation

s applied to assure orthagonality while maximizing the amount ofariation explained by each component.

esults and discussion

aquiladora concentration

Hoover index values for Chihuahua indicate high levels of con-entration in each of the three maquiladora variables, Ma (A), EA) and V (A) (Table 2). They indicate that 94.3% of Chihuahua’s

aquiladora establishments would have had to relocate to otherunicipios in the State in 1980 and 1990 to create uniform distri-

utions of maquiladora establishments. Eighty-nine percent wouldave had to relocate in 2000 to create a uniform distribution. Thepatio-temporal patterns of the other maquiladora variables cor-elate strongly with the number of maquiladora establishments,xhibiting a high degree of concentration. Concentration has beenreatest in Juarez, followed by Chihuahua, since 1970.

opulation concentration

Chihuahua’s total population, P (A), was concentrated in970—approximately 54% of its total population would have hado relocate to other municipios to create a uniform population dis-ribution (Table 2). More important than concentration for a singleate, however, is that population became increasingly concentrated

n the State over time.Disaggregated Hoover index values show that Juarez was the

ain locus of population concentration each decade, and that itsegree of concentration consistently increased over time (Fig. 3).few municipios consistently had near uniform population dis-

(A) 78.00 77.93 80.81 83.66(P) 34.27 31.58 33.02 34.32(A) 75.59 77.66 78.42 80.52(P) 24.43 21.59 16.79 13.40(R) 70.70 72.33 74.26 76.71(A) 56.50 67.46 71.09 75.05(P) 3.76 11.21 8.94 7.83(NW) 4.89 14.27 12.46 11.63

(A) 68.06 72.97 75.46 78.31(P) 16.40 17.08 14.02 11.53(W) 13.42 6.69 5.62 5.04

dashed line indicates periods for which data are unavailable.

540 N. Currit, W.E. Easterling / Land Use Policy 26 (2009) 535–544

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ig. 3. The decadal, spatial pattern of total population concentration, P (A), measopulation concentrated within the area. Darker colors indicate greater concentratot densities mean greater deconcentration.

Importantly, Table 3 shows that the municipio level pattern ofotal population concentration is highly correlated with the munici-io level pattern of maquiladora concentration. These coefficientsndicate a significant, positive, and strong relationship between thewo patterns of concentration. Indeed, for the case of Chihuahua’sotal population, the evidence is strong that the population is con-entrated at the State level and that at the municipio level the totalopulation concentrates where maquiladoras are located.

Measures of migrant population concentration are similar tohose of the total population. All measures of the migrant popula-ion indicate increasing spatial concentration at the state level from980 onward (Table 2). The increases in M (A) concentration begann 1980 and continued to increase to such a degree that in 2000pproximately 84% of the migrant population in Chihuahua wouldave had to be redistributed to other municipios to create a uniformistribution of migrants throughout the State of Chihuahua. The

(P) concentration indices indicate that migrants have becomencreasingly concentrated in highly populated municipios since980. A lag in the statewide concentration of the migrant popula-ion within the total population, until more than a decade after thestablishment of the maquiladora program, seems evident and cor-esponds with the 1980s period of rapid growth in the maquiladorandustry and national economic restructuring.

Migrants, M (A), are most concentrated spatially in Juarez, andver time become increasingly concentrated there (Fig. 4). Over theame periods that migrants concentrated in Juarez, the total num-

er of other municipios with concentrations of migrants decreasedi.e., fewer municipios with solid colors on the maps). Migrants, MP), also became more spatially concentrated within the populationf Juarez—a continually larger proportion of Juarez’s population is

able 3pearman Rank correlation coefficients

1980 1990 2000

(A) 0.831 (0.0001) 0.869 (0.0001) 0.854 (0.0001)(A) 0.922 (0.0001) 0.925 (0.0001) 0.908 (0.0001)(P) 0.326 (0.0072) 0.251 (0.0403) 0.219 (0.0758)(A) 0.910 (0.0001) 0.910 (0.0001) 0.890 (0.0001)(P) 0.355 (0.0032) 0.334 (0.0058) 0.346 (0.0041)(R) 0.355 (0.0032) 0.334 (0.0058) 0.346 (0.0041)(A) 0.896 (0.0001) 0.902 (0.0001) 0.882 (0.0001)(P) 0.340 (0.0049) 0.404 (0.0007) 0.401 (0.0008)

(A) 0.912 (0.0001) 0.911 (0.0001) 0.890 (0.0001)(P) 0.471 (0.0001) 0.473 (0.0001) 0.513 (0.0001)(W) 0.531 (0.0001) 0.332 (0.0060) 0.399 (0.0008)

ach of the 11 rows of the table shows the decadal correlation coefficients betweendisaggregated Hoover concentration index and the disaggregated Hoover index ofaquiladora concentration. Significance levels are indicated in parentheses.

wteptohouctl

n

iotCa

using the disaggregated Hoover index. Municipios with a solid color have a totalunicipios with dots have a total population deconcentrated within the area. Lower

ade up of migrants. This is expected because of the large con-entration of maquiladoras in Juarez and its proximity to the USorder. These numbers indicate that within the State of Chihuahuaeople migrate to Juarez and not other places.3 Migrants in otherunicipios are increasingly rare.

The correlation coefficients indicate that the M (A) con-entration strongly correlates with the pattern of maquiladoraoncentration—0.922, 0.925 and 0.908 in 1980, 1990 and 2000,espectively (Table 3). These numbers support our hypothesis thathihuahua’s migrant population is concentrated where maquilado-as are located. Surprisingly, the correlation coefficients for the

(P) concentration decreases in strength and significance overime. The cause of this unexpected result is that the municipiof Chihuahua, where the State capital is located, is an outlier.t has a large total population, but a relatively small percent-ge of the state’s migrant population. It is, therefore, slightlyeconcentrated, yet it has maquiladoras (Fig. 4). Over the periodxamined, Chihuahua’s total population increases at a rate greaterhan its migrant population, leading to greater deconcentrationn the municipio and weakening correlation M (P)–Ma (A) coeffi-ients.

Some urban population trends are similar to the trends pre-iously discussed, while other trends highlight an urban patternhat is less associated with maquiladora concentration. The U (A)oncentration measures all indicate high and increasing concen-rations at the state and municipio levels that strongly correlateith patterns of maquiladora concentration. This trend is identical

o those already described. The state level U (P) trends, how-ver, are relatively small and decrease over time, indicating aattern approaching uniformity. This pattern occurred for at leastwo reasons. First, the total population concentrated more rapidlyver time than the urban population (the urban population wasighly concentrated initially), leading to decreasing indices. Sec-nd, a number of municipios besides Juarez and Chihuahua haverban population concentrations. The result is that U (P)–Ma (A)orrelation coefficients are weak, a finding that ostensibly con-

radicts the hypothesis of concentration where maquiladoras areocated.

The U (R) concentration trends point to another possible expla-ation for the decreasing U (P) index values. The U (R) indices

3 Mexican census data only indicate the number of native and non-native peoplen a municipio. They do not include information on non-native people’s place ofrigin, or on people that immigrated to the United States. Census information onhe US side, however, indicates a large flow of Mexican migrants in areas borderinghihuahua. Therefore, it should be recognized that people not only go to Juarez, butlso cross the border into the US.

N. Currit, W.E. Easterling / Land Use Policy 26 (2009) 535–544 541

F over it greateL

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ig. 4. Spatial patterns of migrant population concentrations using disaggregated Hoheir area, M (A) (top), or total population, M (P) (bottom). Darker colors indicateower dot densities mean greater deconcentration.

easure the segregation of rural and urban populations. Increas-ng index values indicate an increase in segregation, meaning thewo populations are less frequently found in the same municipio.unicipios are dominated by either rural or urban populations,

ut rarely is there an equal balance of rural and urban popula-ions within a municipio. Thus, the U (R) indices provide evidencef a rural-urban population imbalance. Interestingly, there areeveral municipios with urban population concentrations, albeitmaller concentrations than Juarez or Chihuahua. These munici-ios contain established urban centers that continue to attractrban populations in smaller amounts. Thus, established city cen-ers are likely an additional driver of concentration at the municipioevel.

The U (P)–Ma (A) and U (R)–Ma (A) correlation coefficientsre low because the municipio of Chihuahua is an outlier. It hasaquiladoras, but with a disproportionately small proportion of

he urban population. These coefficients suggest that, regardlessf the presence of maquiladoras, Juarez attracts migrants moretrongly than Chihuahua. This is evidence that people are attractedo Juarez for reasons other than the presence of maquiladoras, likelyecause it has long been an important population center next to aajor US city.The employed population trends are similar to the urban popu-

ation trends. The employed population consists of all economicallyctive people, not just those employed by maquiladoras. The stateevel W (A) indices show concentration over time, with concentra-ion greatest in the municipio of Juarez. Other municipios becamencreasingly deconcentrated. The small and decreasing W (P) trends

ndicate that the employed population is found throughout thetate in equal proportion to the total population. The number of jobsn Juarez may be greater than other municipios, but employment isimilar in all municipios, and becoming more similar. Limited jobpportunities in rural municipios likely encourages migration to

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ndices. Municipios with solid colors have a migrant population concentrated withinr concentration. Municipios with dots have a deconcentrated migrant population.

uarez, and employment rates not significantly different in Juarezay push migrants to the US.

ncome concentration

Income has become increasingly concentrated in the State ofhihuahua, following the pattern of population concentration. In970, 68% of the state’s total income would have had to be redis-ributed to other regions to create a uniform distribution of income.y 2000 that number increased to 78% (Table 2). The greatest con-entration of income was in Juarez, followed closely by Chihuahua.he remaining, mostly rural, municipios of the State have a dimin-shing percentage of the State’s income, a pattern coincident withhe employed population concentration. These trends share signif-cant, strong correlations with trends in the maquiladora industry,ndicating the influence of maquiladoras on income concentrationTable 3).

Income concentrations within the total population, I (P), indi-ate an increasingly uniform income distribution at the state andunicipio levels (Table 2; Fig. 5). Income is always slightly concen-

rated in the population of Juarez, but as the maquiladora programas developed, income has become less concentrated there. In000, all municipios have similar disaggregated I (P) concentra-ion values. An exception to this pattern is Chihuahua, whereoncentration increased. Correlation coefficients show significant,oderately strong I (P)–Ma (A) relationships.These income trends have important implications for rural

egions of the state. Rural areas lack the income found in Juarez

nd few opportunities exist in rural areas to enhance income (seeiscussion on the employed population). Therefore, opportunitiesor rural livelihoods and well-being are restricted by limited avail-bility of total income. Furthermore, while Juarez has more totalob opportunities and a greater concentration of total income than

542 N. Currit, W.E. Easterling / Land Use Policy 26 (2009) 535–544

F s. Muo Municd

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ig. 5. Spatial pattern of income concentrations using disaggregated Hoover indicer total population, I (P) (bottom). Darker colors indicate greater concentration.econcentration.

hihuahua and the rural municipios, its per capita income is nearlyqual to those municipios. These trends imply that migration outf rural regions is likely driven by the perception that there areore job opportunities available in Juarez, even though there is

ot greater per capita income. Migration to Juarez is not likely anancial solution to rural livelihood problems and, once in Juarez,igrants may continue to the US in search of improved livelihoods.

rincipal components analysis

Two principle components (PCs) are extracted from the datasetsor each decadal census (i.e., not the concentration indices). Theigenvalues, rotated loadings matrix and factor scores for eachecade are nearly identical. Therefore, average values are reportedor simplicity. On average, PC1 accounts for 60.50% of the total vari-nce in the dataset and PC2 accounts for 39.42%. The percent of theotal variance explained by each component for each decadal cen-

us never varies from the average by more than 0.46% and 0.50%or principal components 1 and 2, respectively. The average rotatedoadings matrix indicates positive correlation coefficients betweenhe components and each variable (Table 4). The loadings are par-icularly strong between PC1 and the total (0.829), urban (0.807),

able 4verage (1970–2000) rotated component matrix

Component

1 2

otal 0.826 0.563igrant 0.555 0.832rban 0.814 0.580mployed 0.822 0.569ncome 0.834 0.550

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nicipios with solid colors have incomes concentrated within their area, I (A) (top),ipios with dots have deconcentrated incomes. Lower dot densities mean greater

nd employed (0.840) populations and income (0.815). Coefficientsre also strong between PC2 and the migrant population (0.829).hese average coefficients never vary by more than 0.027 and 0.042rom any decadal census.

Mapping the factor scores of each municipio provides additionalnsight into the meaning of each component. The following munici-ios, listed in descending order, score high on PC1: Chihuahua,uarez, Cuauhtémoc, Delicias, Hidalgo del Parral and Nuevo Casasrandes. Each of these municipios has a relatively large, estab-

ished city that is the center of municipal administration (and Statedministration, in the case of Chihuahua). Each has a larger totalopulation than its neighboring municipios. Each provides manyervices to its residents that are not available in smaller communi-ies. Therefore, we label PC1 “established cities.”

In contrast to the many municipios that load highly on PC1, onlyuarez scores high on PC2. Positive, small scores exist for municipiosn each side of Juarez along the border, and in the southeast cornerf the State along a major highway connecting Chihuahua to dis-ance metropolises like Monclova, Coahuila and Monterrey, Nuevoeon. This pattern suggests that PC2 primarily represents the majorigrant destination in the State, namely Juarez. It additionally rep-

esents the influence of proximity to the US border (i.e., in the casef Juarez and its neighbors) and the influence of major transporta-ion routes between Mexican cities (i.e., in the case of Chihuahua’southeast corner). Therefore, we label PC2 “proximity to US-Mexicoorder or major transportation route.”

onclusions

The purpose of this article was to examine population andncome patterns at regional and local levels within the State of Chi-uahua and to test whether or not forces of globalization coulde detected in the patterns. We hypothesize that a unique rural-

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N. Currit, W.E. Easterling / La

rban pattern of population and income (de)concentration withinhihuahua has emerged as globally interconnected Ciudad Juarez

nteracts with the other municipios in the state. We test for the influ-nce of globalization on these patterns by examining their spatialovariance with patterns of maquiladora concentration. We explainhe patterns we see as emergent properties arising from interact-ng processes between adjacent levels in a hierarchical system. Ino doing, we answer where and why population and income areoncentrating in Chihuahua. These patterns reveal the complexityf land-use processes due to globalization in Chihuahua.

The maquiladora program is an indicator of globalizationor Mexico because its establishment marked an increase inlobal interconnectedness between Mexico and other countriesia multi-national corporations and consumers across the globe.ts establishment occurred in conjunction with industrial andopulation deconcentration trends away from Mexico City andhe termination of the Bracero Program in the US. Historically,hihuahua’s maquiladoras were located primarily in Juarez. Theighest concentration is still in Juarez, but five municipios hadaquiladoras in 2000 and the total number has risen dramatically

ince 1965.Maquiladoras are fueled by international capital and operate in

global market, but they strongly influence change at local andegional scales as part of a dynamic hierarchical system. As such,lobalization is the broadest scale in our hierarchy of interaction.t manifests itself locally in the form of maquiladoras. Individual

unicipios are the finest scale in our hierarchy. Our scale of inter-st is Chihuahua State; not at an aggregate level, but at the levelf interaction among its municipios as driven by concentration inhe maquiladora industry. Our findings show that population andncome land-use patterns emerge from the interaction of global-zation forces and individual municipios.

Growth in the maquiladora industry drives changes in the con-entration of population and income at the municipio level inegions near and far from the location of maquiladoras. Almostithout exception, findings indicate that all population categories

xhibit patterns of increasing concentration at the state level in Chi-uahua. The municipio where population concentration is greatest

s Juarez, followed distantly by Chihuahua. As of 2000, nearly 40% ofhe State’s population lived in Juarez and 20% lived in Chihuahua.n contrast, rural municipios of the State exhibit, almost withoutxception, a pattern of deconcentration over time. The concentra-ion of migrants in Juarez has increased greatly since the beginningf the maquiladora program. Migrants in rural regions are rare.indings suggest that municipios distant from Ciudad Juarez areource regions of population for Juarez.

Not surprisingly, income concentration patterns closely trackhose of population concentration, demonstrating that total avail-ble income in rural municipios is decreasing. Decreases in totalvailable income limit economic opportunities in rural municipiosnd likely foster declines in rural infrastructure, livelihoods andellbeing. The result is additional pressure to migrate to placeshere job availability is perceived to be greater. A crucial finding,owever, is that job formation is outpaced by population growth

n Juarez. There is a larger proportion of the population that ismployed in Juarez than in other municipios of the State, but notuch larger. The result is an increasingly uniform distribution of

he employed population across the State since 1980. Likewise, perapita income concentration is not much greater in Ciudad Juarezhan it is in other municipios, and it, too, has become more uniformly

istributed across the State over time. That is, per capita incomesre not significantly higher in Juarez than in rural municipios. Itollows that the same incentives that drive people to leave rurallaces in order to improve wellbeing and livelihood opportunities

n Juarez likely also exist in Juarez.

leufc

e Policy 26 (2009) 535–544 543

Spearman Rank correlation coefficients indicate that spatial pat-erns of population and income concentration covary with thepatial pattern of maquiladora concentration over time. Thesendings support the hypothesis that maquiladora concentration

eads to population and income concentration in places whereaquiladoras are located and simultaneously leads to deconcen-

ration in rural regions distant from the location of maquiladoras.The general pattern of covariance evident in most municipios

s not perfect, however. While population was deconcentrating inost municipios except Juarez, there were municipios where cer-

ain population categories remained slightly concentrated, notablyhe urban population. Based on the concentration and maquiladora

easures used, these municipios appear less coupled to globaliza-ion. These places appear to serve as secondary loci of concentrationn a hierarchy where globally connected Juarez is at the top. The

unicipio of Chihuahua is an example of this because its popula-ion experienced limited concentration even though it experiencedrowth in the maquiladora industry. Other places, like the munici-ios of Nuevo Casas Grandes and Cuauhtémoc, became slightlyore concentrated in terms of population and income (and theyere consistently more concentrated than their neighbors). Theseunicipios experienced concentration even though they are less

trongly tied to patterns and processes of globalization as reflectedy their involvement in the maquiladora industry. Principal compo-ents analysis further indicates that established urban centers androximity to the US-Mexico border or a major transportation routere additional underlying causes of population concentration.

The patterns described support our conceptualization ofopulation land-use and income dynamics in Chihuahua as aierarchically organized system. Globalization, measured via theaquiladora industry, appears to abet an emergent pattern of

opulation concentration where maquiladoras are located and aimultaneous deconcentration in regions distant from maquilado-as. This emergent pattern cannot be fully explained by changesn economic strategies designed to increase Mexico’s global com-etitiveness. It cannot be fully explained by the termination ofhe US Bracero program and the inception of the BIP. It cannote fully explained by the activities or changes unique to individ-al maquiladoras or municipios. It is best explained by consideringhe simultaneous interaction of these processes to create themergent pattern of urban concentration, rural deconcentration.herefore, these findings validate the conceptualization and use ofrinciples of hierarchically organized systems and provide a mech-nism for assessing the impact of external perturbations on theystem.

The resilience of the emergent patterns we describe likelyepends on the sustained interaction of processes from all scales inhe hierarchy. Changes to the processes of any scale may producelternate emergent patterns. For example, maquiladora produc-ion drastically dropped recently and the long-term viability ofhe maquiladora industry has been called into question (Sargentnd Matthews, 2003). Possible causes of the production declinenclude economic slowdown in the US, NAFTA driven changeso import duties, and changes in Mexican tax laws (Sargent and

atthews, 2003). These possible causes are external perturbationso the maquiladora industry and thus indirect perturbations to themergent patterns we describe. How vulnerable is the system toxternal perturbations? Will population and income concentra-ion slow down, or perhaps reverse? Presently, maquiladoras haveot disappeared and population and income concentration will

ikely persist in Juarez and remain low in rural municipios. Also, theffects of established urban centers and proximity to the US remainnderlying factors behind the pattern we describe. Nevertheless,uture work should examine these and other perturbations morelosely.

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44 N. Currit, W.E. Easterling / La

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